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Fitting in a group: Theoretical development and validation of the Multidimensional Perceived Person–Group Fit scale
Author(s) -
Li Christina S.,
KristofBrown Amy L.,
Nielsen Jordan D.
Publication year - 2018
Publication title -
personnel psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.076
H-Index - 142
eISSN - 1744-6570
pISSN - 0031-5826
DOI - 10.1111/peps.12295
Subject(s) - psychology , scale (ratio) , congruence (geometry) , social psychology , similarity (geometry) , discriminant validity , clarity , dimension (graph theory) , multidimensional scaling , perception , psychometrics , statistics , developmental psychology , artificial intelligence , mathematics , computer science , internal consistency , biochemistry , chemistry , physics , quantum mechanics , neuroscience , pure mathematics , image (mathematics)
Despite the wide use of groups in organizations, research on individuals’ experiences of fit in their work groups has lagged due to lack of conceptual clarity of person–group (PG) fit and inconsistent measurement. To rectify these issues, we present an integrative definition of PG fit, which incorporates social‐ and task‐related elements of group work, as well as supplementary and complementary conceptualizations of fit. Using this definition, we develop the Multidimensional Perceived Person‐Group Fit (MPPGF) scale and validate it through five phases, across six samples. In Phase 1, we identified dimensions and generated items using a mix of deductive and inductive approaches. In Phase 2, we validated items yielding seven dimensions (value congruence, shared interests, perceived demographic similarity, needs‐supplies match, goal similarity, common workstyle, and complementary attributes). In Phase 3, we examined how the dimensions combine to form an aggregate (formative) PG fit construct. The MPPGF scale showed convergent and discriminant validity with relevant constructs in Phase 4. In Phase 5, the MPPGF exhibited criterion‐related and incremental validity with attitudes and performance beyond existing PG fit scales. Finally, we report dimension‐specific results, demonstrating that MPPGF could be used to study questions regarding overall PG fit perceptions, as well as more narrow dimension‐specific questions.